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Data lineage tracks the origin, movement, and transformation of data as it flows through systems. It answers questions like: Where did this number come from? What transformations were applied? Which systems depend on it?
In BI environments, data lineage provides transparency and accountability. When a dashboard metric looks wrong, lineage helps teams trace the issue back to its source.
Data lineage typically shows:
Source systems
Transformation steps
Intermediate tables
Final datasets and dashboards
Downstream dependencies
Lineage can be:
Technical lineage: system-level data flow
Business lineage: metric-level definitions and logic
Modern BI and data catalog tools automatically capture lineage metadata from pipelines, warehouses, and BI tools.
Data lineage is essential for:
Debugging data issues
Impact analysis
Compliance and auditing
Change management
AI explainability
Without lineage, analytics teams struggle to understand dependencies and risks, breaking downstream reports when changes are made.
In mature analytics organizations, lineage is integrated into daily workflows, enabling faster troubleshooting and safer iteration.




